Energy Space Layout

Abstract

The current housing market in the Netherlands depicts a need for energy-efficient buildings for young professionals. Performative Computational Architecture (PCA), as computational methodology, is a valuable source of knowledge and design support to integrate the buildings’ performances at early stages. By applying PCA, this thesis explores and optimises the correlation between space layout and energy performance of a co-living residence in the Netherlands. Firstly, a generic model is developed to gain initial findings, then, is applied to a case-study to evaluate its practicability. The study considers a mixed-mode building with adaptive thermal comfort models and optimises three objectives distinctively: the cooling, the heating and the lighting demands.
The results provide both computational and energy-efficient insights, useful to achieve performance-driven designs. Despite the main influence of the envelope parameters on the energy demand, it is beneficial to plan the functions in order to fulfil their energy and comfort requirements. Different functions play the leading roles in minimising different objectives, varying the depth, the orientation and the windows accordingly. In shallow buildings, energy-optimised configurations can save more than 37% of the total energy demand. However, the results are strictly dependent on the solution space defined by the parametric model. In practice, the designer needs to translate the underlying principles of space layout or to develop a site-specific optimisation.